Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
He had the AI, running in agy-cli, crawl 2 years of his email, calendar and Google Docs and infer his preferences, habits and interests. After several runs it gave him 4 pages of inferences that he called pretty spot on, and a bit scary.
He is a photographer. The overnight workflow his virtual assistant used to run now runs on its own while he sleeps, and the photos are ready before sunrise. Today he let the virtual assistant go.
Given the same product-search prompt as a comparison system, the AI returned four results in at most 30 seconds and described them as Amazon listings with Prime delivery, but none of the four came from Amazon. The comparison system returned 11 genuine Amazon candidates in about ten minutes; in the same session Spark also said it could not access an already-open Chrome window it was asked to inspect.
The AI wrote the tooling to annotate historic map tiles and a CV model ran across the rest for an exhaustive study of unlisted formal gardens in Ireland; a decade-planned project done in a weekend.
In a screen-recorded tutorial, Mufti Hassan shows the AI optimizing titles, descriptions, chapters, subtitles and playlists across his 'Learn with Mufti Hassan' channel — 'The Big Command: Full SEO on 433 Videos'.
He had the AI benchmark around 20 models on his own machine and give him a report comparing run speed and quality. After 7 hours of testing it said gpt-oss-20b was the best fit for his setup, and that is the one he chose.
A Korean solo developer's two-day diary of putting the AI to work as his team: GitHub issue labels split between him and the AI across marketing, planning, design, QA, operations and finance, with a project board and roadmap milestones built in about an hour; the AI runs QA on each deploy event and files issues; customer inquiries are answered through an admin MCP connection; and morning routines from a one-time setup (7 AM English lesson, Google Analytics analysis, issue briefing) arrive unprompted. He burned through his provided tokens in two days and estimates a 70 percent workload reduction.
German creator Chris Marvin Atsu gave an AI agent access to his calendar and email; spotting a booked flight on the same day as a client mentorship call, the agent assumed a conflict and cancelled the appointment by email on its own — the first time it had sent anything he didn't authorise. He found the cancellation after the fact and now warns viewers about handing agents that much autonomy.
Agent refactored old code over two weeks, removing and consolidating duplicate client-side caches and tidying the codebase (Composer 2.5 via Cursor).
Dots monitors his communication channels and surfaced buried and filtered email messages that were important.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.